Digital Health Technologies in Breast Cancer Management

Abstract

Breast cancer remains the most frequently diagnosed malignancy among women worldwide and continues to be a leading cause of cancer-related morbidity and mortality despite substantial advances in screening, molecular diagnostics, targeted therapies, and precision medicine. The rapid evolution of digital health technologies has transformed breast cancer care by enabling more personalized, data-driven, and patient-centered management throughout the entire continuum of care. Artificial intelligence (AI), telemedicine, wearable biosensors, mobile health applications, digital pathology, electronic health records, cloud computing, digital therapeutics, remote patient monitoring, and digital twin technologies are increasingly integrated into breast oncology to improve early detection, diagnosis, treatment planning, therapeutic monitoring, survivorship care, and clinical decision support. Machine learning, deep learning, computer vision, multimodal learning, natural language processing, and predictive analytics facilitate automated analysis of radiological imaging, genomic sequencing, pathology, laboratory investigations, and longitudinal clinical data, thereby supporting precision medicine. Furthermore, digital platforms improve healthcare accessibility, multidisciplinary collaboration, patient engagement, and real-time monitoring while reducing healthcare costs and optimizing clinical workflows. Despite these advances, challenges remain regarding interoperability, cybersecurity, patient privacy, digital literacy, algorithmic bias, regulatory oversight, and equitable implementation. This review discusses the evolving role of digital health technologies in breast cancer management, highlighting current clinical applications, emerging innovations, implementation challenges, and future perspectives for digitally enabled precision breast oncology.